This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. A challenge in post-genomic biology is to develop a truly integrated computational platform that allows intelligent retrieval and analysis of any available genomic-scale or single-gene information. Due to difficulties in integrating heterogeneous data types, for example due to the lack of a uniform standard in data annotation, coping with continuous updating of existing databases or with disparate confidence levels associated with different data sets, most biological databases are focused on a specific subset of biological knowledge. At present, a biologist must retrieve the data by querying individual databases, and must integrate, filter and visualize the data herself for obtaining comprehensive biological information. To facilitate this process, we recently constructed PathSys, a data integration platform that provides dynamic integration over diverse databases containing genetic, molecular interactions, localization, and microarray data available through published literature.